Papers with Code 아카이브

Object Detection

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전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yahidar/radarformer

공식 코드

RadarFormer: Lightweight and Accurate Real-Time Radar Object Detection Model

https://github.com/yan-hao-tian/ConTNet

공식 코드

ConTNet: Why not use convolution and transformer at the same time?

https://github.com/yancie-yjr/StreamYOLO

공식 코드

Real-time Object Detection for Streaming Perception

https://github.com/yancie-yjr/dbq-ssd

공식 코드

DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection

https://github.com/yang-0201/MAF-YOLO

공식 코드

Multi-Branch Auxiliary Fusion YOLO with Re-parameterization Heterogeneous Convolutional for accurate object detection

https://github.com/yang-0201/mhaf-yolo

공식 코드

MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detection

https://github.com/yang-song/APDLM

공식 코드

Training Deep Neural Networks via Direct Loss Minimization

https://github.com/yang-yk/NP-RepMet

공식 코드

Restoring Negative Information in Few-Shot Object Detection

https://github.com/yangcao1996/fanet

공식 코드

FakeMix Augmentation Improves Transparent Object Detection

https://github.com/yangcaoai/3dgs-det

공식 코드

3DGS-DET: Empower 3D Gaussian Splatting with Boundary Guidance and Box-Focused Sampling for 3D Object Detection

https://github.com/yangcaoai/CoDA_NeurIPS2023

공식 코드

Collaborative Novel Object Discovery and Box-Guided Cross-Modal Alignment for Open-Vocabulary 3D Object Detection

https://github.com/yangfan-hu/fast-snn

공식 코드

Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN

https://github.com/yanghai-1218/radet

공식 코드

Rigidity-Aware Detection for 6D Object Pose Estimation

https://github.com/yanghtr/ssgnet

공식 코드

LiDAR-Based 3D Object Detection via Hybrid 2D Semantic Scene Generation

https://github.com/yanglei18/Lite-FPN

공식 코드

Lite-FPN for Keypoint-based Monocular 3D Object Detection

https://github.com/yanglei18/mix-teaching

공식 코드

Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection

https://github.com/yanglei18/sgv3d

공식 코드

SGV3D:Towards Scenario Generalization for Vision-based Roadside 3D Object Detection

https://github.com/yangli18/pdnet

공식 코드

PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling

https://github.com/yangli18/vltvg

공식 코드

Improving Visual Grounding with Visual-Linguistic Verification and Iterative Reasoning

https://github.com/yangtiming/imov3d

공식 코드

ImOV3D: Learning Open-Vocabulary Point Clouds 3D Object Detection from Only 2D Images

https://github.com/yangxu351/synthetic_xview_airplanes

공식 코드

SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems

https://github.com/yangxue0827/RotationDetection

공식 코드

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

https://github.com/yangxue0827/STAR-MMRotate

공식 코드

STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery

https://github.com/yangxue0827/h2rbox-jittor

공식 코드

H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection

https://github.com/yangxue0827/h2rbox-mmrotate

공식 코드

H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection

https://github.com/yangxue0827/rsg-mmrotate

공식 코드

STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery

https://github.com/yangyang-69/Prompt_sam_cryoPPP

공식 코드

Adapting Segment Anything Model (SAM) through Prompt-based Learning for Enhanced Protein Identification in Cryo-EM Micrographs

https://github.com/yangyanggirl/bos

공식 코드

Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments

https://github.com/yangyangyang127/pointclip_v2

공식 코드

PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning

https://github.com/yangzhaojason/DualDiff

공식 코드

DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward Guidance

https://github.com/yaohungt/Demystifying_Self_Supervised_Learning

공식 코드

Self-supervised Learning from a Multi-view Perspective

https://github.com/yaorong0921/driver-gaze-yolov5

공식 코드

Where and What: Driver Attention-based Object Detection

https://github.com/ybkscht/EfficientPose

공식 코드

EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach

https://github.com/ybzh/point-dae

공식 코드

Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning

https://github.com/yc-zh/wsvm

공식 코드

Weakly Supervised Object Detection for Automatic Tooth-marked Tongue Recognition

https://github.com/ycyinchao/rdvp-msd

공식 코드

Stepwise Decomposition and Dual-stream Focus: A Novel Approach for Training-free Camouflaged Object Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.